Fuzzy Neural Networks Adaptive Control of Micro Gas Turbine with Prediction Model
Ft. Lauderdale, FL（2006）
摘要
This paper proposes a control method for nonlinear models realized in the form of implicit rule-based fuzzy neural networks (FNN). The design of the model dwells on fuzzy sets and neural networks. The rotation speed control scheme of a single shaft gas turbine used in power generation is discussed. A fuzzy neural controller based on the prediction model is designed and the simulation is conducted by Matlab/Simulink. It is shown that by tuning the fuzzy neural network controller (FNNC), the performance of the system can be achieved in a wide range of operating conditions compared to the fuzzy logic controller and fuzzy PID controller (F-PID). It indicates that the controller has satisfactory adaptive ability and robustness. The controller improves the control effectiveness of gas turbine system
更多查看译文
关键词
power generation,robustness,fuzzy set theory,neurocontrollers,robust control,rotation speed control scheme,implicit rule-based fuzzy neural networks,single shaft gas turbine,velocity control,fuzzy sets,adaptive control,microgas turbine,nonlinear control systems,fuzzy logic controller,nonlinear models,fuzzy neural network controller,fuzzy control,power generation control,gas turbines,prediction model,fuzzy neural nets,fuzzy pid controller,fuzzy neural networks adaptive control,fuzzy set,neural network,fuzzy neural network,operant conditioning,speed control,pid controller,rule based
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要